172 lines
6.8 KiB
C++
172 lines
6.8 KiB
C++
/*
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* Copyright (c) 2018-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "arm_compute/core/Types.h"
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#include "src/core/CL/kernels/CLCol2ImKernel.h"
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#include "tests/CL/CLAccessor.h"
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#include "tests/CL/Helper.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/datasets/Datasets.h"
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#include "tests/validation/Validation.h"
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#include "tests/validation/fixtures/Col2ImFixture.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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TEST_SUITE(CL)
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TEST_SUITE(Col2Im)
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using CLCol2Im = CLSynthetizeFunction<CLCol2ImKernel>;
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/** Negative tests
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*
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* A series of validation tests on configurations which according to the API specification
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* the function should fail against.
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*
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* Checks performed in order:
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* - Pass unsupported data type for input
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* - Pass NHWC as output data layout
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* - Pass an invalid output shape
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*/
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TEST_CASE(Negative, framework::DatasetMode::ALL)
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{
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// Unsupported data type
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{
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const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::SIZET);
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const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32);
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const auto conv_size = Size2D(3, 4);
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const auto status = CLCol2ImKernel::validate(&input, &output, conv_size);
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ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
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}
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// NHWC as output data layout
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{
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const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32);
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const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32, DataLayout::NHWC);
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const auto conv_size = Size2D(3, 4);
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const auto status = CLCol2ImKernel::validate(&input, &output, conv_size);
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ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
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}
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// Invalid output size
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{
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const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32);
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const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 2U, 2U), 1, DataType::F32);
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const auto conv_size = Size2D(3, 4);
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const auto status = CLCol2ImKernel::validate(&input, &output, conv_size);
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ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
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}
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}
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template <typename T>
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using CLCol2ImFixture = Col2ImValidationFixture<CLTensor, CLAccessor, CLCol2Im, T, true>;
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/** Test kernel for single-precision floating point
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*
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* @note 8 elements processed per iteration
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*
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* Three main tests will be run:
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* - Channels are multiple of elements processed
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* - Channels larger and non multiple of elements used
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* - Channels smaller and not multiple of elements used
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*
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* The above will be repeated with a different group size
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*
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* Kernel tested col2im
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*/
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FIXTURE_DATA_TEST_CASE(FP32,
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CLCol2ImFixture<float>,
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framework::DatasetMode::ALL,
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combine(combine(combine(combine(
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framework::dataset::make("InputShape", { TensorShape(8U, 16U, 3U, 1U), TensorShape(17U, 16U, 3U, 1U), TensorShape(7U, 16U, 3U, 1U) }),
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framework::dataset::make("ConvolvedWidth", 4)),
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framework::dataset::make("ConvolvedHeight", 4)),
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framework::dataset::make("Groups", { 1, 3 })),
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framework::dataset::make("DataType", DataType::F32)))
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{
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// Validate output
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validate(CLAccessor(_target), _reference);
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}
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/** Test kernel for half-precision floating point
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*
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* @note 8 elements processed per iteration
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*
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* One main tests will be run:
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* - Channels larger and non multiple of elements used
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*
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* We just need to test the difference in the data type size.
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* Any other issues can be identified by the main FP32 tests
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*
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* Kernel tested col2im
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*/
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FIXTURE_DATA_TEST_CASE(F16,
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CLCol2ImFixture<half>,
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framework::DatasetMode::ALL,
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combine(combine(combine(combine(
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framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)),
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framework::dataset::make("ConvolvedWidth", 4)),
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framework::dataset::make("ConvolvedHeight", 4)),
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framework::dataset::make("Groups", 3)),
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framework::dataset::make("DataType", DataType::F16)))
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{
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// Validate output
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validate(CLAccessor(_target), _reference);
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}
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/** Test kernel for unsigned asymmetric quantized type
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*
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* @note 8 elements processed per iteration
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*
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* One main tests will be run:
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* - Channels larger and non multiple of elements used
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*
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* We just need to test the difference in the data type size.
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* Any other issues can be identified by the main FP32 tests
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*
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* Kernel tested col2im
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*/
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FIXTURE_DATA_TEST_CASE(QASYMM8,
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CLCol2ImFixture<uint8_t>,
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framework::DatasetMode::ALL,
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combine(combine(combine(combine(
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framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)),
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framework::dataset::make("ConvolvedWidth", 4)),
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framework::dataset::make("ConvolvedHeight", 4)),
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framework::dataset::make("Groups", 3)),
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framework::dataset::make("DataType", DataType::QASYMM8)))
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{
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// Validate output
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validate(CLAccessor(_target), _reference);
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}
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TEST_SUITE_END() // CL
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TEST_SUITE_END() // Col2Im
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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